Roadie, a UPS Company, is a logistics management and crowdsourced delivery platform. Founded in 2014, Roadie offers businesses fast, flexible and asset-light logistics solutions for last-mile delivery. Roadie enables local delivery to more than 95% of U.S. households by providing access to more than 200,000 independent drivers nationwide – allowing businesses to offer their customers delivery optionality for almost any industry, from airlines to artisans.

As a Machine Learning Engineer at Roadie, you will build algorithms and models that run our core systems, from matching deliveries and drivers in a two-sided market, to routing optimizations and dynamic pricing schemes. Collaborating with Software Engineers and Data Scientists, you will create technology that solves real-world problems in the crowdsourced delivery space. This position will initially be focused on machine learning capabilities with marketplace pricing.

What You’ll Do

• Design, build and maintain new machine learning pipelines at the intersection of crowdsourced systems and logistics
• Creatively apply the state of the art in machine learning to optimize Roadie’s automated decision-making
• Build new pricing solutions for our expanding delivery marketplace
• Work with engineering, product and design on a cross functional team to implement the pipelines in a production environment
• Advocate for data driven decision making throughout the company 

What You Bring

• MS or PhD in Machine Learning, Artificial Intelligence, Statistics, Computer Science, Operations Research or a related field
• 2+ years of experience with applied machine learning
• Extensive hands-on experience with Python and SQL
• Expertise in machine learning algorithms (unsupervised and supervised) and statistical methods
• Experience in evaluating model performance
• Experience using machine learning in the context of logistics 
• Familiarity with libraries such as Pandas, Numpy, Scikit-Learn, SciPy, PyTorch, Tensorflow, Keras and related
• Understanding of modern deep learning techniques such as CNN, RNN
• Ability to effectively articulate technical challenges and solutions to multiple audiences

Bonus

• Experience with graph algorithms
• Experience with combinatorial or nonlinear optimization techniques
• Experience with containers, Docker, or Kubernetes
• Experience with cloud environments such as AWS, GCP, or Azure
• Experience building machine learning pipelines and full loop machine learning systems
• Experience with dynamic programming, approximate dynamic programming, and/or optimal control theory

Why Roadie? 

• Competitive compensation packages 
• 100% covered health insurance premiums for yourself
• 401k with company match
• Tuition and student loan repayment assistance (that’s right - Roadie will contribute directly to your existing student loans!) 
• Flexible work schedule with unlimited PTO 
• Monthly 3-day weekends
• Monthly WFH stipend 
• Paid sabbatical leave- tenured team members are given time to rest, relax, and explore
• The technology you need to get the job done

This role is not eligible for Visa sponsorship. Applicants must be authorized to work for any employer in the U.S.